Abstract

Mountain wave breaking in the lower stratosphere is one of the major causes of atmospheric turbulence encountered in commercial aviation, which in turn is the cause of most weather-related aircraft incidents. In the case of clear air turbulence (CAT), there are no visual clues and pilots are reliant on operational forecasts and reports from other aircraft. Traditionally mountain waves have been sub-grid-scale in global numerical weather prediction (NWP) models, but recent developments in NWP mean that some forecast centres (e.g. the UK Met Office) are now producing operational global forecasts that resolve mountain wave activity explicitly, allowing predictions of mountain wave induced turbulence with greater accuracy and confidence than previously possible. Using a bespoke turbulent kinetic energy diagnostic, the Met Office Unified Model (MetUM) is shown to produce useful forecasts of mountain CAT during three case studies over Greenland, and to outperform the current operational Met Office CAT prediction product (the World Area Forecast Centre (WAFC) London gridded CAT product) in doing so. In a long term, 17-month, verification, MetUM forecasts yield a turbulence prediction hit rate of 80% with an accompanying false alarm rate of under 40%. These skill scores are a considerable improvement on those reported for the mountain wave component of the WAFC product, although no direct comparison is available. The major implication of this work is that sophisticated global NWP models are now sufficiently advanced to provide skilful forecasts of mountain wave turbulence.